沙特阿拉伯COVID-19传播和控制机制的数学模型。

IF 4.1 3区 数学 Q1 Mathematics
Advances in Difference Equations Pub Date : 2021-01-01 Epub Date: 2021-05-14 DOI:10.1186/s13662-021-03410-z
Mostafa Bachar, Mohamed A Khamsi, Messaoud Bounkhel
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引用次数: 12

摘要

在这项工作中,我们开发并分析了沙特阿拉伯新型冠状病毒病(COVID-19)传播的非自治数学模型。该模型包括八个时间相关的区室:低风险S L和高风险S M易感个体的动态;暴露个体隔间E;感染个体的隔室(分为两个隔室,即未确诊感染个体I U和确诊感染个体I D);恢复未诊断个体R U的室室,恢复诊断R D个体的室室,灭绝Ex个体的室室。考虑到当局施加的控制措施,我们研究了持久性和局部稳定性,包括模型的复制数。我们根据COVID-19流行病学数据(包括COVID-19传播不同时间段里的感染、恢复和灭绝个体的数量),在大流行总持续时间的短时间内进行参数估计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A mathematical model for the spread of COVID-19 and control mechanisms in Saudi Arabia.

A mathematical model for the spread of COVID-19 and control mechanisms in Saudi Arabia.

A mathematical model for the spread of COVID-19 and control mechanisms in Saudi Arabia.

A mathematical model for the spread of COVID-19 and control mechanisms in Saudi Arabia.

In this work, we develop and analyze a nonautonomous mathematical model for the spread of the new corona-virus disease (COVID-19) in Saudi Arabia. The model includes eight time-dependent compartments: the dynamics of low-risk S L and high-risk S M susceptible individuals; the compartment of exposed individuals E; the compartment of infected individuals (divided into two compartments, namely those of infected undiagnosed individuals I U and the one consisting of infected diagnosed individuals I D ); the compartment of recovered undiagnosed individuals R U , that of recovered diagnosed R D individuals, and the compartment of extinct Ex individuals. We investigate the persistence and the local stability including the reproduction number of the model, taking into account the control measures imposed by the authorities. We perform a parameter estimation over a short period of the total duration of the pandemic based on the COVID-19 epidemiological data, including the number of infected, recovered, and extinct individuals, in different time episodes of the COVID-19 spread.

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来源期刊
自引率
0.00%
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0
审稿时长
4-8 weeks
期刊介绍: The theory of difference equations, the methods used, and their wide applications have advanced beyond their adolescent stage to occupy a central position in applicable analysis. In fact, in the last 15 years, the proliferation of the subject has been witnessed by hundreds of research articles, several monographs, many international conferences, and numerous special sessions. The theory of differential and difference equations forms two extreme representations of real world problems. For example, a simple population model when represented as a differential equation shows the good behavior of solutions whereas the corresponding discrete analogue shows the chaotic behavior. The actual behavior of the population is somewhere in between. The aim of Advances in Difference Equations is to report mainly the new developments in the field of difference equations, and their applications in all fields. We will also consider research articles emphasizing the qualitative behavior of solutions of ordinary, partial, delay, fractional, abstract, stochastic, fuzzy, and set-valued differential equations. Advances in Difference Equations will accept high-quality articles containing original research results and survey articles of exceptional merit.
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